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Received: 2022/02/21 | Accepted: 2022/05/12 | Published: 2022/07/1
Received: 2022/02/21 | Accepted: 2022/05/12 | Published: 2022/07/1
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Gharakhani A, Hashemi H, Chalajour M. Factors Affecting the Realization of Employment Policies in the Agricultural Sector in Bahar City, Hamadan Province, Iran. GeoRes 2022; 37 (3) :429-438
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1- Department of Agricultural Economics, Faculty of Economics, Roodehen Branch, Islamic Azad University, Iran
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Introduction
To move toward achieving sustainable development goals, appropriate growth in key socio-economic indicators is essential. The adjustment of macro-level quantitative and qualitative indicators in line with development policies is therefore of great importance. Two of the most critical macro indicators are the reduction of income inequality and the increase in employment rates. Achieving sustainable development goals requires identifying the employment-generating capacities of different economic sectors, reducing income inequality, and efficiently directing productive resources toward these sectors [Salami & Ansari, 2009]. Employment is one of the most important parameters in a macroeconomic model, and any change in this parameter exerts specific effects on other economic parameters. Employment is a fundamental social need, and any deficiency in this area can give rise to numerous economic, social, and cultural problems [Mohammadi et al., 2014]. Today, employment and unemployment constitute major issues in the economic development literature of all countries. Employment is the primary source of household income and a key mechanism for poverty alleviation, whereas rising unemployment contributes to slower economic growth and increased social problems. Iran is currently facing a severe employment and unemployment crisis, marked by a worrying imbalance between labor supply and demand. Given the country’s young population structure, neglecting employment issues may turn into a major challenge for the Iranian economy, leading to higher unemployment and adverse consequences [Norozi et al., 2018].
In Iran, the agricultural sector, following the service sector, is the largest economic sector, accounting for approximately 26% of gross domestic product and 26% of non-oil exports. From a historical perspective, industrial production emerged after agricultural production. Ricardo argued that agricultural progress enhances overall economic productivity and that the limitations of agricultural growth determine the boundaries of this sector’s expansion and the necessity of capital formation for economic development. Accordingly, at the early stages of industrial growth in any country, the role and position of agriculture are highly decisive. Subsequently, the interaction and dynamic linkage between the agricultural and industrial sectors become increasingly important [Khorrami, 2017].
Among various economic sectors, agriculture possesses distinctive characteristics that have consistently attracted attention with respect to employment and, in particular, income distribution. This sector is not only crucial for ensuring national food security, but also contributes to the growth of other sectors by supplying raw materials to related industries. Moreover, agricultural growth improves welfare, income levels, and food security among rural populations, who largely belong to lower-income deciles, and helps prevent rural-to-urban migration and the expansion of urban marginalization [Salami & Ansari, 2009; Bakeshloo et al., 2022]. Several studies have emphasized the positive relationship between increased agricultural productivity and economic growth, proposing agriculture as a highly effective instrument for promoting economic growth and combating poverty in developing countries [Self & Grabowski, 2007]. As one of the strategic sectors in the development trajectories of different countries, agriculture has held particular importance across various periods. Evidence from development experiences suggests that agricultural development, as one of the most important economic sectors, or even beyond that, is a fundamental prerequisite for achieving sustainable national development. Without addressing development barriers in this sector, progress and prosperity in other sectors, including industry, cannot be expected [Zand & Mosavi, 2022].
Given that agricultural employment is predominantly held by rural populations, rural residents can be considered a key factor in the success of agricultural development [Hafez et al., 2020]. Employment in agriculture contributes to a dynamic balance aligned with rural values and improves rural livelihoods [Rahmon Ibrahim, 2014]. Accordingly, from the perspective of the European :union:, achieving rural and economic development in many developing countries requires progress in agricultural development [Whitfield et al., 2015].
Iran is among the countries where the traditional agricultural production system, due to economic inefficiencies, is unable to adequately meet national needs. Economic conditions continue to pose numerous challenges for farmers, consumers, and investors in the agricultural sector [Chizari & Vazirian, 2022]. Declining employment in rural areas and the agricultural sector has led to adverse outcomes, including reduced rural incomes, increased inequality and poverty, rural-to-urban migration, and higher labor concentration in urban areas. These developments negatively affect socio-economic, environmental, and behavioral indicators. Socially, rural migration to urban areas contributes to rising unemployment, poverty, and inequality, while environmentally it promotes suburbanization and increased population density. From a behavioral perspective, these factors foster delinquency and income-related social tensions.
In recent decades, industrial growth, urban expansion, and the development of service sectors, coupled with insufficient attention to agriculture and rural areas in Iran, have driven labor migration from rural to urban regions. This process has resulted in urban unemployment and widened income disparities between rural and urban areas. It should be noted that rural areas play a vital role in the national production and employment system. In agriculture, production expansion depends on the use of labor, capital, land, and management. Improving the efficiency of this sector is made possible through the application of new knowledge, a favorable economic environment, and appropriate production incentives. Development theorists argue that, in the early stages of development, agriculture supplies surplus resources, generates employment, and provides essential food. The failure of economic policies in countries that attempted to achieve growth by neglecting agriculture and relying solely on industry led to the emergence of new theoretical perspectives. Since the 1960s, economists such as Johnson and Mellor have increasingly emphasized the importance of agriculture in economic development. Ultimately, Schultz’s theory of the transition from traditional agriculture played a significant role in refuting claims regarding the insignificance of investment in agriculture. Based on historical development performance and empirical evidence from many developing countries, he demonstrated the potential for substantial growth through investment in agriculture and identified limited technical knowledge among farmers, technological backwardness, and insufficient investment as key constraints on agricultural development [Mohammadi et al., 2014].
In analyses of labor demand, agricultural subsectors have been shown to exert a positive and significant effect on labor demand [Amini, 2002]. Compared with other economic sectors, agriculture offers several advantages for employment generation, including compatibility between employment development and the dispersed distribution of rural populations, lower costs of job creation relative to industry, greater ease of integration into global markets, the potential for qualitative improvement of agricultural production systems within existing national capacities, lower requirements for specialized training, retention of rural populations in rural areas, and strong multiplier effects in entrepreneurship and job creation [Mazandarani, 2004]. Consequently, the formulation of appropriate employment policies for the agricultural sector is of particular importance. Achieving employment policy objectives depends on multiple influencing factors, and since job seekers consider a wide range of conditions when choosing employment, attention to these determinants is essential.
Given the importance of agricultural employment in western Iran, and considering that agricultural employment is influenced by both upstream and downstream factors that evolve over time and interact with one another, examining the socio-economic determinants of employment in the agricultural sector is especially important. Accordingly, the objective of this study was to investigate the factors affecting employment generation in the agricultural sector of Hamedan Province.
Methodology
This study employed a survey design with a mixed-methods (quantitative–qualitative) approach and was conducted in 2021. The study area was Bahar County in Hamedan Province. Owing to its economic and socio-social capacities, available facilities, and agricultural production resources, Hamedan Province is considered one of Iran’s important provinces. Despite certain constraints, such as inefficiencies in labor skills, the agricultural sector of Hamedan benefits from relatively effective mechanization, an educated workforce, and a young rural population. At the same time, rural areas of the province are facing rapid population growth alongside challenges related to employment and entrepreneurship, making youth entrepreneurship particularly significant.
Hamedan Province covers an area of 20,173 square kilometers and consists of nine counties, 35 districts, 30 cities, 73 rural districts, and 1,120 villages. Its agricultural lands are of suitable quality and high productive capacity, ranking first nationally in the production of walnuts and potatoes. Bahar County, located approximately 15 kilometers west of Hamedan city, covers 1,739 square kilometers, accounting for about 6.9% of the province’s total area. Among the counties of Hamedan Province, Bahar holds the leading position in the production and export of agricultural products such as potatoes, plums, tomatoes, cucumbers, and mushrooms. The county comprises three districts, six rural districts, and four cities: Bahar, Lalejin, Salehabad, and Mohajeran. Given its soil potential, climatic conditions, and agricultural capabilities—particularly in agro-processing industries—Bahar County is regarded as one of the prominent agricultural areas of the province. Approximately 60,000 hectares of irrigated and rain-fed cereal crops and about 1,300 hectares of garlic cultivation are located in this county. Due to its importance in agricultural production and its considerable capacity for employment generation, Bahar County was selected as the case study for this research.
The primary research instrument was a researcher-designed questionnaire developed based on semi-structured interviews conducted using an expert-based approach. The purpose of this phase was to collect expert opinions in the field of agriculture regarding factors influencing employment generation in Hamedan Province. Experts were selected through purposive non-random sampling, resulting in 47 participants. The study framework, objectives, and expected duration were explained to all participants. Each interview lasted approximately 45 minutes and, with participants’ consent, was audio-recorded and later transcribed verbatim.
Data coding and analysis were carried out using the grounded theory approach. Interview transcripts were carefully reviewed to ensure accuracy, and all data were coded in detail. Conceptually similar data segments were grouped together based on defined concepts representing shared meanings among the initial codes. The codes were repeatedly reviewed and refined to identify main categories and their subcategories. Based on this process, an initial questionnaire consisting of 20 items was designed using a five-point Likert scale ranging from “strongly agree” to “strongly disagree.” During the expert review stage, redundant items were removed and similar items were merged, and questions were reformulated to encompass multiple related concepts in order to reduce the total number of items to an acceptable level. For instance, items related to economic dimensions were consolidated due to their conceptual similarity.
To assess the necessity and adequacy of the questionnaire items, content validity measures were applied. The questionnaire was reviewed by 37 experts, who evaluated each item in terms of its necessity and relevance. Subsequently, the reliability of the research instrument was assessed using Cronbach’s alpha coefficient.
In the questionnaire distribution phase, the statistical population consisted of 5,899 farmers and agricultural operators residing in the rural areas of Bahar County. The sample size was determined from this population, resulting in a sample of 250 respondents selected through random sampling. The questionnaire was structured using a five-point Likert scale ranging from “agree” to “strongly disagree.” Data were analyzed using descriptive statistical methods with SPSS software.
To prioritize factors and evaluate interrelationships among them, a network-based decision-making approach was employed. This approach conceptualizes the research problem as a network of criteria, sub-criteria, and alternatives grouped into clusters, allowing for interdependencies and feedback among elements both within and between clusters. The analytical process included model development, pairwise comparisons to determine relative importance, synthesis of priorities, and identification of the most influential alternatives. In this study, the analytical framework was designed across three levels: the overall goal, evaluation criteria, and alternatives. The criteria comprised four main dimensions derived from content analysis. Prioritization of criteria and selection of optimal alternatives were conducted using both hierarchical and network-based analytical perspectives, enabling consideration of feedback effects among criteria and alternatives.
Findings
The demographic information of the respondents indicated that 17.9% were single and 82.1% were married. Thus, engagement in agricultural employment was higher among married individuals. The age group 30–40 years accounted for 33.4% of respondents, representing the largest share, while the 40–50 years group represented the smallest share at 18.3%, indicating that agricultural employment was more prevalent among younger individuals. Agricultural experience of 5–10 years was reported by 45.6% of respondents, higher than other experience ranges, suggesting that mid-career farmers were the most active participants.
Reliability of the questionnaire was assessed using Cronbach’s alpha, while content validity was evaluated through the content validity index (CVI) and content validity ratio (CVR). The results indicated acceptable reliability and validity for all criteria, including economic, social, environmental, and behavioral dimensions.
Among economic factors influencing agricultural employment and entrepreneurship, sub-criteria such as adequate credit distribution, crop insurance, low-interest loans, and capital shortage were identified as most important. Providing financial support and credit facilities enhances farmers’ ability to secure labor, capital, and necessary inputs, thereby increasing agricultural value-added and employment. A positive stock of agricultural capital enables efficient utilization of equipment, labor, and land, enhancing productivity, covering production costs, generating appropriate returns on investment, and potentially expanding domestic supply and exports. Therefore, direct and indirect effects of financial support on agricultural employment are significant.
Regarding social factors, collaboration with relevant institutions and perseverance at work were prioritized. Participation in planning processes is critical because agricultural employment development depends on motivation and continuous learning. The more extensive the involvement of local people, stakeholders, and decision-making institutions in policy development and implementation, the more practical and effective the employment strategies will be.
In terms of environmental factors, soil quality and personal experience were ranked highest. Factors such as crop type selection, crop rotation, and soil enhancement techniques (e.g., fertilization) significantly affect agricultural outcomes. The effectiveness of such methods depends largely on proper knowledge, personal experience, and education.
Among behavioral factors, opportunity recognition and decision-making were the most significant for farmers. Correct decision-making in crop selection, awareness of value addition, and timing of planting, cultivation, and harvest in response to climatic changes enhances profitability and motivates employment in agriculture. Other behavioral sub-criteria such as work motivation, life satisfaction, satisfaction with agricultural work, and responsibility were also influential.
Overall, economic criteria had the highest priority (0.556) in influencing employment in Bahar County, followed by environmental (0.270), social (0.252), and behavioral (0.201) criteria. Based on the ANP model, economic factors ranked first with 72% importance, followed by environmental factors with a 9% difference. The network model, which incorporates feedback among criteria and sub-criteria, provided more precise results due to the consideration of interdependencies. Differences between the hierarchical and network analysis methods were minimal, with the lowest rank in the hierarchical model observed in behavioral criteria, while in the ANP model the lowest influence was slightly shifted to environmental factors.
The ANP model results showed only slight differences in the ranking of sub-criteria compared to the hierarchical analysis. For example, in economic criteria, low-interest loans and lack of capital held the highest and lowest ranks, respectively. In social criteria, access to information and individual creativity were at the highest and lowest ranks. For environmental criteria, soil quality and available facilities were ranked highest and lowest, respectively. In behavioral criteria, life satisfaction and work conscientiousness had the highest and lowest ranks.
Discussion
This study examined the factors influencing employment in the agricultural sector of Bahar County, Hamadan Province.
Based on the findings, economic factors have the greatest impact on agricultural employment compared to other factors. Among the economic sub-criteria, credit allocation holds the highest priority. Given that 82% of respondents were married, attention to improving economic conditions and implementing strategies to enhance life satisfaction in households headed by farmers is essential. Increasing bank credit allocation to agriculture promotes growth in the sector, which in turn contributes to employment. Despite gaps in the current credit system, such as insufficient access for small-scale farmers, providing credit remains a key mechanism to support agricultural production. Access to credit allows for higher input consumption, greater investment, and ultimately increased production. In Iran, the importance of credit is further emphasized due to factors such as rationing, the high-risk nature of agricultural activities, and the low income of small farming units. Consequently, a portion of the government budget is annually allocated to financing agriculture. The direct and indirect relationship between increased credit and employment in agriculture, as well as the success of employment policies, has been highlighted in previous studies [Parva et al., 2021; Das & Joice, 2009; Bostan et al., 2021; Azimi, 2013; Chizari & Vazirian, 2022].
Another economic factor is the provision of low-interest loans. Recently, policymakers have focused on allocating microcredits and low-interest loans to increase employment. Such loans directly and indirectly enhance agricultural production, farmers’ capital, and employment, thereby contributing to rural development and improved life satisfaction among villagers. For instance, Balali and Khalilian [2003] have emphasized the role of agricultural investment in job creation. There is a direct and indirect interaction among the criteria studied in this research: higher loan interest rates and reduced credit allocation diminish motivation, self-confidence, responsibility, job satisfaction, and life satisfaction in behavioral sub-criteria. Conversely, small loan amounts and short repayment periods may fail to sufficiently motivate recipients to invest in productive activities and create employment in agriculture. These findings align with prior studies [Abdi et al., 2020; Udoka et al., 2019; Makombe et al., 1999; Bakeshloo et al., 2022].
Iran’s agricultural sector faces a surplus labor force (skilled and unskilled), and based on production economics principles, increasing labor productivity requires increasing other inputs, namely land and capital. Since land is limited, the remaining option is to increase capital. The positive relationship between investment and employment can be linked to complementary factors such as expanding cultivated area. Investment in this sector and application of efficient methods can reduce unemployment in both the short and long term. However, attracting and directing capital to agriculture faces multiple obstacles. Compared to other economic sectors, agriculture is labor-intensive, and increased investment introduces advanced technologies and mechanization. While mechanization may boost employment in other sectors such as industry and services, it reduces direct labor demand in agriculture due to the replacement of human labor by machinery. Balali and Khalilian have noted that negative impacts of capital on employment may result from wage imbalances between labor and machinery, where higher wages relative to machine use encourage substitution. Adjusting labor wages relative to machinery costs is therefore crucial for regulating labor demand and employment in agriculture, consistent with findings by Esfandabadi & Javdan [2010] and Balali & Khalilian [2003].
In the socio-cultural dimension, access to information, perseverance, creativity, interest in self-employment, education, and participation with relevant institutions were identified as influential sub-criteria for agricultural employment. Participation with institutions and perseverance had the highest and lowest ranks, respectively, in both hierarchical and ANP models. Farmers with perseverance and self-employment interest demonstrated higher motivation and efforts to improve conditions. Greater perseverance fosters interest in agriculture, better management, and planning skills, enhancing self-efficacy and promoting employment. Training programs on farm management and operational planning can strengthen perseverance, self-efficacy, motivation, and interest in agricultural self-employment, as supported by Maleksaeedi et al. [2009].
Participation with decision-making and policy institutions increases farmers’ confidence and strengthens behavioral dimensions. Without community involvement, responsibility, planning, and development cannot be realized. Participation plays a significant role in promoting agricultural employment and rural development, enabling individuals and groups to influence employment policies and improve quality of life, in line with findings by Sharifinia [2020] and Onabestani [2013].
Behavioral parameters influencing employment are largely shaped by family, community, socio-economic status, and policy. Motivated individuals are better able to identify opportunities and utilize environmental facilities. For example, self-employment motivation facilitates access to social networks necessary for entrepreneurship. A supportive business environment enhances access to facilities, expands social networks among entrepreneurs, and strengthens entrepreneurial motivation. Behavioral parameters interact, so improving one positively affects others. To foster motivation for agricultural employment, factors such as life satisfaction, job satisfaction, and responsibility must be maintained at adequate levels, which themselves are influenced by economic, environmental, and socio-cultural criteria.
Achieving employment policy objectives in a region depends on multiple factors, making attention to these factors essential. Khorrami [2015] also concluded that agriculture ranks seventh in direct employment creation, highlighting the need to focus on factors influencing employment in this sector. Economic, social, environmental, and behavioral factors influencing agricultural employment are interrelated. Economic factors, in particular, play the most important role; improving economic conditions through public and private support positively affects other employment-related criteria. Increased working capital provides access to agricultural tools and resources and enhances environmental parameters. Economic improvement promotes socio-cultural indicators, self-employment, and education, while also boosting confidence, self-efficacy, responsibility, and work motivation among individuals interested in agriculture.
Conclusion
Multiple factors influence the achievement of employment policy objectives. The findings of this study indicate that economic factors are the most influential in promoting employment in the agricultural sector. Other social-cultural, environmental, and behavioral factors also affect employment in this sector, in that order. Considering the availability of natural resources, human capital, and the critical role of rural areas in agriculture, a comprehensive approach addressing economic, social, environmental, and behavioral factors is essential. Additionally, creating conditions for both material and non-material support and fostering a greater inclination toward agricultural employment in Bahar County is necessary.
Acknowledgments: The authors report no acknowledgments.
Ethical Permission: The authors report no ethical approval required.
Conflict of Interest: The authors declare no conflict of interest.
Authors’ Contributions: Gharakhani A (first author), Introduction Writer/Statistical Analyst/Main Researcher (40%); Hashemi H (second author), Methodologist (30%); Chalajour M (third author), Discussion Writer (30%)
Funding: All expenses were independently covered by the authors.
To move toward achieving sustainable development goals, appropriate growth in key socio-economic indicators is essential. The adjustment of macro-level quantitative and qualitative indicators in line with development policies is therefore of great importance. Two of the most critical macro indicators are the reduction of income inequality and the increase in employment rates. Achieving sustainable development goals requires identifying the employment-generating capacities of different economic sectors, reducing income inequality, and efficiently directing productive resources toward these sectors [Salami & Ansari, 2009]. Employment is one of the most important parameters in a macroeconomic model, and any change in this parameter exerts specific effects on other economic parameters. Employment is a fundamental social need, and any deficiency in this area can give rise to numerous economic, social, and cultural problems [Mohammadi et al., 2014]. Today, employment and unemployment constitute major issues in the economic development literature of all countries. Employment is the primary source of household income and a key mechanism for poverty alleviation, whereas rising unemployment contributes to slower economic growth and increased social problems. Iran is currently facing a severe employment and unemployment crisis, marked by a worrying imbalance between labor supply and demand. Given the country’s young population structure, neglecting employment issues may turn into a major challenge for the Iranian economy, leading to higher unemployment and adverse consequences [Norozi et al., 2018].
In Iran, the agricultural sector, following the service sector, is the largest economic sector, accounting for approximately 26% of gross domestic product and 26% of non-oil exports. From a historical perspective, industrial production emerged after agricultural production. Ricardo argued that agricultural progress enhances overall economic productivity and that the limitations of agricultural growth determine the boundaries of this sector’s expansion and the necessity of capital formation for economic development. Accordingly, at the early stages of industrial growth in any country, the role and position of agriculture are highly decisive. Subsequently, the interaction and dynamic linkage between the agricultural and industrial sectors become increasingly important [Khorrami, 2017].
Among various economic sectors, agriculture possesses distinctive characteristics that have consistently attracted attention with respect to employment and, in particular, income distribution. This sector is not only crucial for ensuring national food security, but also contributes to the growth of other sectors by supplying raw materials to related industries. Moreover, agricultural growth improves welfare, income levels, and food security among rural populations, who largely belong to lower-income deciles, and helps prevent rural-to-urban migration and the expansion of urban marginalization [Salami & Ansari, 2009; Bakeshloo et al., 2022]. Several studies have emphasized the positive relationship between increased agricultural productivity and economic growth, proposing agriculture as a highly effective instrument for promoting economic growth and combating poverty in developing countries [Self & Grabowski, 2007]. As one of the strategic sectors in the development trajectories of different countries, agriculture has held particular importance across various periods. Evidence from development experiences suggests that agricultural development, as one of the most important economic sectors, or even beyond that, is a fundamental prerequisite for achieving sustainable national development. Without addressing development barriers in this sector, progress and prosperity in other sectors, including industry, cannot be expected [Zand & Mosavi, 2022].
Given that agricultural employment is predominantly held by rural populations, rural residents can be considered a key factor in the success of agricultural development [Hafez et al., 2020]. Employment in agriculture contributes to a dynamic balance aligned with rural values and improves rural livelihoods [Rahmon Ibrahim, 2014]. Accordingly, from the perspective of the European :union:, achieving rural and economic development in many developing countries requires progress in agricultural development [Whitfield et al., 2015].
Iran is among the countries where the traditional agricultural production system, due to economic inefficiencies, is unable to adequately meet national needs. Economic conditions continue to pose numerous challenges for farmers, consumers, and investors in the agricultural sector [Chizari & Vazirian, 2022]. Declining employment in rural areas and the agricultural sector has led to adverse outcomes, including reduced rural incomes, increased inequality and poverty, rural-to-urban migration, and higher labor concentration in urban areas. These developments negatively affect socio-economic, environmental, and behavioral indicators. Socially, rural migration to urban areas contributes to rising unemployment, poverty, and inequality, while environmentally it promotes suburbanization and increased population density. From a behavioral perspective, these factors foster delinquency and income-related social tensions.
In recent decades, industrial growth, urban expansion, and the development of service sectors, coupled with insufficient attention to agriculture and rural areas in Iran, have driven labor migration from rural to urban regions. This process has resulted in urban unemployment and widened income disparities between rural and urban areas. It should be noted that rural areas play a vital role in the national production and employment system. In agriculture, production expansion depends on the use of labor, capital, land, and management. Improving the efficiency of this sector is made possible through the application of new knowledge, a favorable economic environment, and appropriate production incentives. Development theorists argue that, in the early stages of development, agriculture supplies surplus resources, generates employment, and provides essential food. The failure of economic policies in countries that attempted to achieve growth by neglecting agriculture and relying solely on industry led to the emergence of new theoretical perspectives. Since the 1960s, economists such as Johnson and Mellor have increasingly emphasized the importance of agriculture in economic development. Ultimately, Schultz’s theory of the transition from traditional agriculture played a significant role in refuting claims regarding the insignificance of investment in agriculture. Based on historical development performance and empirical evidence from many developing countries, he demonstrated the potential for substantial growth through investment in agriculture and identified limited technical knowledge among farmers, technological backwardness, and insufficient investment as key constraints on agricultural development [Mohammadi et al., 2014].
In analyses of labor demand, agricultural subsectors have been shown to exert a positive and significant effect on labor demand [Amini, 2002]. Compared with other economic sectors, agriculture offers several advantages for employment generation, including compatibility between employment development and the dispersed distribution of rural populations, lower costs of job creation relative to industry, greater ease of integration into global markets, the potential for qualitative improvement of agricultural production systems within existing national capacities, lower requirements for specialized training, retention of rural populations in rural areas, and strong multiplier effects in entrepreneurship and job creation [Mazandarani, 2004]. Consequently, the formulation of appropriate employment policies for the agricultural sector is of particular importance. Achieving employment policy objectives depends on multiple influencing factors, and since job seekers consider a wide range of conditions when choosing employment, attention to these determinants is essential.
Given the importance of agricultural employment in western Iran, and considering that agricultural employment is influenced by both upstream and downstream factors that evolve over time and interact with one another, examining the socio-economic determinants of employment in the agricultural sector is especially important. Accordingly, the objective of this study was to investigate the factors affecting employment generation in the agricultural sector of Hamedan Province.
Methodology
This study employed a survey design with a mixed-methods (quantitative–qualitative) approach and was conducted in 2021. The study area was Bahar County in Hamedan Province. Owing to its economic and socio-social capacities, available facilities, and agricultural production resources, Hamedan Province is considered one of Iran’s important provinces. Despite certain constraints, such as inefficiencies in labor skills, the agricultural sector of Hamedan benefits from relatively effective mechanization, an educated workforce, and a young rural population. At the same time, rural areas of the province are facing rapid population growth alongside challenges related to employment and entrepreneurship, making youth entrepreneurship particularly significant.
Hamedan Province covers an area of 20,173 square kilometers and consists of nine counties, 35 districts, 30 cities, 73 rural districts, and 1,120 villages. Its agricultural lands are of suitable quality and high productive capacity, ranking first nationally in the production of walnuts and potatoes. Bahar County, located approximately 15 kilometers west of Hamedan city, covers 1,739 square kilometers, accounting for about 6.9% of the province’s total area. Among the counties of Hamedan Province, Bahar holds the leading position in the production and export of agricultural products such as potatoes, plums, tomatoes, cucumbers, and mushrooms. The county comprises three districts, six rural districts, and four cities: Bahar, Lalejin, Salehabad, and Mohajeran. Given its soil potential, climatic conditions, and agricultural capabilities—particularly in agro-processing industries—Bahar County is regarded as one of the prominent agricultural areas of the province. Approximately 60,000 hectares of irrigated and rain-fed cereal crops and about 1,300 hectares of garlic cultivation are located in this county. Due to its importance in agricultural production and its considerable capacity for employment generation, Bahar County was selected as the case study for this research.
The primary research instrument was a researcher-designed questionnaire developed based on semi-structured interviews conducted using an expert-based approach. The purpose of this phase was to collect expert opinions in the field of agriculture regarding factors influencing employment generation in Hamedan Province. Experts were selected through purposive non-random sampling, resulting in 47 participants. The study framework, objectives, and expected duration were explained to all participants. Each interview lasted approximately 45 minutes and, with participants’ consent, was audio-recorded and later transcribed verbatim.
Data coding and analysis were carried out using the grounded theory approach. Interview transcripts were carefully reviewed to ensure accuracy, and all data were coded in detail. Conceptually similar data segments were grouped together based on defined concepts representing shared meanings among the initial codes. The codes were repeatedly reviewed and refined to identify main categories and their subcategories. Based on this process, an initial questionnaire consisting of 20 items was designed using a five-point Likert scale ranging from “strongly agree” to “strongly disagree.” During the expert review stage, redundant items were removed and similar items were merged, and questions were reformulated to encompass multiple related concepts in order to reduce the total number of items to an acceptable level. For instance, items related to economic dimensions were consolidated due to their conceptual similarity.
To assess the necessity and adequacy of the questionnaire items, content validity measures were applied. The questionnaire was reviewed by 37 experts, who evaluated each item in terms of its necessity and relevance. Subsequently, the reliability of the research instrument was assessed using Cronbach’s alpha coefficient.
In the questionnaire distribution phase, the statistical population consisted of 5,899 farmers and agricultural operators residing in the rural areas of Bahar County. The sample size was determined from this population, resulting in a sample of 250 respondents selected through random sampling. The questionnaire was structured using a five-point Likert scale ranging from “agree” to “strongly disagree.” Data were analyzed using descriptive statistical methods with SPSS software.
To prioritize factors and evaluate interrelationships among them, a network-based decision-making approach was employed. This approach conceptualizes the research problem as a network of criteria, sub-criteria, and alternatives grouped into clusters, allowing for interdependencies and feedback among elements both within and between clusters. The analytical process included model development, pairwise comparisons to determine relative importance, synthesis of priorities, and identification of the most influential alternatives. In this study, the analytical framework was designed across three levels: the overall goal, evaluation criteria, and alternatives. The criteria comprised four main dimensions derived from content analysis. Prioritization of criteria and selection of optimal alternatives were conducted using both hierarchical and network-based analytical perspectives, enabling consideration of feedback effects among criteria and alternatives.
Findings
The demographic information of the respondents indicated that 17.9% were single and 82.1% were married. Thus, engagement in agricultural employment was higher among married individuals. The age group 30–40 years accounted for 33.4% of respondents, representing the largest share, while the 40–50 years group represented the smallest share at 18.3%, indicating that agricultural employment was more prevalent among younger individuals. Agricultural experience of 5–10 years was reported by 45.6% of respondents, higher than other experience ranges, suggesting that mid-career farmers were the most active participants.
Reliability of the questionnaire was assessed using Cronbach’s alpha, while content validity was evaluated through the content validity index (CVI) and content validity ratio (CVR). The results indicated acceptable reliability and validity for all criteria, including economic, social, environmental, and behavioral dimensions.
Among economic factors influencing agricultural employment and entrepreneurship, sub-criteria such as adequate credit distribution, crop insurance, low-interest loans, and capital shortage were identified as most important. Providing financial support and credit facilities enhances farmers’ ability to secure labor, capital, and necessary inputs, thereby increasing agricultural value-added and employment. A positive stock of agricultural capital enables efficient utilization of equipment, labor, and land, enhancing productivity, covering production costs, generating appropriate returns on investment, and potentially expanding domestic supply and exports. Therefore, direct and indirect effects of financial support on agricultural employment are significant.
Regarding social factors, collaboration with relevant institutions and perseverance at work were prioritized. Participation in planning processes is critical because agricultural employment development depends on motivation and continuous learning. The more extensive the involvement of local people, stakeholders, and decision-making institutions in policy development and implementation, the more practical and effective the employment strategies will be.
In terms of environmental factors, soil quality and personal experience were ranked highest. Factors such as crop type selection, crop rotation, and soil enhancement techniques (e.g., fertilization) significantly affect agricultural outcomes. The effectiveness of such methods depends largely on proper knowledge, personal experience, and education.
Among behavioral factors, opportunity recognition and decision-making were the most significant for farmers. Correct decision-making in crop selection, awareness of value addition, and timing of planting, cultivation, and harvest in response to climatic changes enhances profitability and motivates employment in agriculture. Other behavioral sub-criteria such as work motivation, life satisfaction, satisfaction with agricultural work, and responsibility were also influential.
Overall, economic criteria had the highest priority (0.556) in influencing employment in Bahar County, followed by environmental (0.270), social (0.252), and behavioral (0.201) criteria. Based on the ANP model, economic factors ranked first with 72% importance, followed by environmental factors with a 9% difference. The network model, which incorporates feedback among criteria and sub-criteria, provided more precise results due to the consideration of interdependencies. Differences between the hierarchical and network analysis methods were minimal, with the lowest rank in the hierarchical model observed in behavioral criteria, while in the ANP model the lowest influence was slightly shifted to environmental factors.
The ANP model results showed only slight differences in the ranking of sub-criteria compared to the hierarchical analysis. For example, in economic criteria, low-interest loans and lack of capital held the highest and lowest ranks, respectively. In social criteria, access to information and individual creativity were at the highest and lowest ranks. For environmental criteria, soil quality and available facilities were ranked highest and lowest, respectively. In behavioral criteria, life satisfaction and work conscientiousness had the highest and lowest ranks.
Discussion
This study examined the factors influencing employment in the agricultural sector of Bahar County, Hamadan Province.
Based on the findings, economic factors have the greatest impact on agricultural employment compared to other factors. Among the economic sub-criteria, credit allocation holds the highest priority. Given that 82% of respondents were married, attention to improving economic conditions and implementing strategies to enhance life satisfaction in households headed by farmers is essential. Increasing bank credit allocation to agriculture promotes growth in the sector, which in turn contributes to employment. Despite gaps in the current credit system, such as insufficient access for small-scale farmers, providing credit remains a key mechanism to support agricultural production. Access to credit allows for higher input consumption, greater investment, and ultimately increased production. In Iran, the importance of credit is further emphasized due to factors such as rationing, the high-risk nature of agricultural activities, and the low income of small farming units. Consequently, a portion of the government budget is annually allocated to financing agriculture. The direct and indirect relationship between increased credit and employment in agriculture, as well as the success of employment policies, has been highlighted in previous studies [Parva et al., 2021; Das & Joice, 2009; Bostan et al., 2021; Azimi, 2013; Chizari & Vazirian, 2022].
Another economic factor is the provision of low-interest loans. Recently, policymakers have focused on allocating microcredits and low-interest loans to increase employment. Such loans directly and indirectly enhance agricultural production, farmers’ capital, and employment, thereby contributing to rural development and improved life satisfaction among villagers. For instance, Balali and Khalilian [2003] have emphasized the role of agricultural investment in job creation. There is a direct and indirect interaction among the criteria studied in this research: higher loan interest rates and reduced credit allocation diminish motivation, self-confidence, responsibility, job satisfaction, and life satisfaction in behavioral sub-criteria. Conversely, small loan amounts and short repayment periods may fail to sufficiently motivate recipients to invest in productive activities and create employment in agriculture. These findings align with prior studies [Abdi et al., 2020; Udoka et al., 2019; Makombe et al., 1999; Bakeshloo et al., 2022].
Iran’s agricultural sector faces a surplus labor force (skilled and unskilled), and based on production economics principles, increasing labor productivity requires increasing other inputs, namely land and capital. Since land is limited, the remaining option is to increase capital. The positive relationship between investment and employment can be linked to complementary factors such as expanding cultivated area. Investment in this sector and application of efficient methods can reduce unemployment in both the short and long term. However, attracting and directing capital to agriculture faces multiple obstacles. Compared to other economic sectors, agriculture is labor-intensive, and increased investment introduces advanced technologies and mechanization. While mechanization may boost employment in other sectors such as industry and services, it reduces direct labor demand in agriculture due to the replacement of human labor by machinery. Balali and Khalilian have noted that negative impacts of capital on employment may result from wage imbalances between labor and machinery, where higher wages relative to machine use encourage substitution. Adjusting labor wages relative to machinery costs is therefore crucial for regulating labor demand and employment in agriculture, consistent with findings by Esfandabadi & Javdan [2010] and Balali & Khalilian [2003].
In the socio-cultural dimension, access to information, perseverance, creativity, interest in self-employment, education, and participation with relevant institutions were identified as influential sub-criteria for agricultural employment. Participation with institutions and perseverance had the highest and lowest ranks, respectively, in both hierarchical and ANP models. Farmers with perseverance and self-employment interest demonstrated higher motivation and efforts to improve conditions. Greater perseverance fosters interest in agriculture, better management, and planning skills, enhancing self-efficacy and promoting employment. Training programs on farm management and operational planning can strengthen perseverance, self-efficacy, motivation, and interest in agricultural self-employment, as supported by Maleksaeedi et al. [2009].
Participation with decision-making and policy institutions increases farmers’ confidence and strengthens behavioral dimensions. Without community involvement, responsibility, planning, and development cannot be realized. Participation plays a significant role in promoting agricultural employment and rural development, enabling individuals and groups to influence employment policies and improve quality of life, in line with findings by Sharifinia [2020] and Onabestani [2013].
Behavioral parameters influencing employment are largely shaped by family, community, socio-economic status, and policy. Motivated individuals are better able to identify opportunities and utilize environmental facilities. For example, self-employment motivation facilitates access to social networks necessary for entrepreneurship. A supportive business environment enhances access to facilities, expands social networks among entrepreneurs, and strengthens entrepreneurial motivation. Behavioral parameters interact, so improving one positively affects others. To foster motivation for agricultural employment, factors such as life satisfaction, job satisfaction, and responsibility must be maintained at adequate levels, which themselves are influenced by economic, environmental, and socio-cultural criteria.
Achieving employment policy objectives in a region depends on multiple factors, making attention to these factors essential. Khorrami [2015] also concluded that agriculture ranks seventh in direct employment creation, highlighting the need to focus on factors influencing employment in this sector. Economic, social, environmental, and behavioral factors influencing agricultural employment are interrelated. Economic factors, in particular, play the most important role; improving economic conditions through public and private support positively affects other employment-related criteria. Increased working capital provides access to agricultural tools and resources and enhances environmental parameters. Economic improvement promotes socio-cultural indicators, self-employment, and education, while also boosting confidence, self-efficacy, responsibility, and work motivation among individuals interested in agriculture.
Conclusion
Multiple factors influence the achievement of employment policy objectives. The findings of this study indicate that economic factors are the most influential in promoting employment in the agricultural sector. Other social-cultural, environmental, and behavioral factors also affect employment in this sector, in that order. Considering the availability of natural resources, human capital, and the critical role of rural areas in agriculture, a comprehensive approach addressing economic, social, environmental, and behavioral factors is essential. Additionally, creating conditions for both material and non-material support and fostering a greater inclination toward agricultural employment in Bahar County is necessary.
Acknowledgments: The authors report no acknowledgments.
Ethical Permission: The authors report no ethical approval required.
Conflict of Interest: The authors declare no conflict of interest.
Authors’ Contributions: Gharakhani A (first author), Introduction Writer/Statistical Analyst/Main Researcher (40%); Hashemi H (second author), Methodologist (30%); Chalajour M (third author), Discussion Writer (30%)
Funding: All expenses were independently covered by the authors.
Keywords:
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